extract_features: Extract features for paw time series

In pawscore: Pain Assessment at Withdrawal Speeds (PAWS)

Extract features for paw time series

Description

Extract features for paw time series

Usage

extract_features(
  x,
  y = NULL,
  parameters = default_parameters(),
  diagnostics = FALSE
)

Arguments

x	time series of horizontal paw movement. Alternatively, a two column matrix of x and y time series, respectively.
y	time series of vertical paw movement, or NULL if x is a two column matrix.
parameters	contains information about frames per second, filtering, windowing, and thresholds, for paw features (see default_parameters, or use set_parameters to modify the defaults).
diagnostics	set to TRUE will record intermediate values used when computing paw features. This information can be helpful for debugging parameter choices. The default, FALSE, is to not record these values.

Value

pre-peak and post-peak paw features (plus diagnostics, if enabled)

Examples

# example usage with a track from Jones et al. (2020)
track    <- jones2020.tracks[[1]]
features <- extract_features(track$time.series)

pawscore documentation built on Sept. 18, 2023, 5:12 p.m.